What limits the effectiveness of DOE? - intellegens By Ben Pellegrini, Intellegens CEO Design of experiments (DOE) seems like a ‘no brainer’ It supports innovation in chemicals, materials, and formulations while saving time and cost In the first of this short series of blogs, we explored these benefits
Three ways AI can switch on battery research - intellegens Joel was discussing how machine learning-led adaptive experimental methods can be applied to speed and inform this research From projects that Intellegens has been involved with, we can highlight three main application areas
Intellegens awarded ISO 27001 information security certification Intellegens has been certified to ISO 27001 standard for its information security systems and practices The award provides crucial assurance to customers and partners as we work together on projects that apply and develop vital intellectual property
Intellegens announces Alchemite™ Suite Cambridge-based Intellegens today announced the Alchemite Suite, a step-change in ease-of-implementation and use for machine learning to accelerate R D
Faster, fewer, better - adaptive DOE - intellegens By Ben Pellegrini, Intellegens CEO How can machine learning make Design of Experiments (DOE) easier and deliver better results? In the first of this short series of blogs, we saw the value of DOE In the second blog, we saw why conventional DOE often falls short
Webinar – Sustainable products and processes with machine learning You’ll also see a demonstration of the Alchemite software from Intellegens, showing how ML can be used to reduce carbon footprint and energy consumption, minimize waste, and design formulations and processes to avoid use of chemicals that are harmful to human health or the environment
Innovation in Oligonucleotide Manufacturing Symposium (29 Apr, Glasgow) The two-year project is augmenting and validating the Alchemite™, technology from Intellegens as as a tool to enhance productivity and yields of oligonucleotide therapeutic manufacture through performance prediction and optimisation of quality control strategies
Artificial Intellegens Newsletter (Sep Oct 2025) It’s question we hear a lot at Intellegens In this white paper, we explore how machine learning adds value to Design of Experiments and why conventional DOE and machine learning should not be seen as competing methods, but as complementary tools
Rapid Residual Stress Simulation and Distortion Mitigation in Laser . . . Intellegens scientist Joel Strickland is a co-author on a new paper that applies machine learning to support a robust tool for predicting residual stresses and mitigating distortion in Laser Powder Bed Fusion (LBPF) processes